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Dorr BJ.  1991.  Machine translation: A principle-based approach. Artificial intelligence at MIT expanding frontiers. :326-361.
Dorr BJ, Hendler J, Blanksteen S, Migdalof B.  1993.  Use of lexical conceptual structure for intelligent tutoring.
Dorr BJ, Lee K.  1992.  Building a lexicon for machine translation: use of corpora for aspectual classification of verbs.
Dorr BJ.  1990.  Solving thematic divergences in machine translation. Proceedings of the 28th annual meeting on Association for Computational Linguistics. :127-134.
Dorr BJ, Marti A, Castellon I.  1998.  Evaluation of EuroWordNet-and LCS-based lexical resources for machine translation. Proceedings from First International Conference on Language Resources & Evaluation. :393-398.
Dorr BJ, Lin D, Lee J, Suh S.  1994.  A paradigm for non-head-driven parsing: Parameterized message-passing. Proceedings of the International Conference on New Methods in Language Processing, Manchester, UK.
Dorr BJ.  1997.  Large-Scale Dictionary Construction for Foreign Language Tutoring and Interlingual Machine Translation. Machine Translation. 12(4):271-322.
Dorr BJ.  1991.  Conceptual Basis of the Lexicon in Machine Translation. Lexical acquisition: exploiting on-line resources to build a lexiconLexical acquisition: exploiting on-line resources to build a lexicon. :263-263.
Dorr BJ.  1997.  LEXICALL: Lexicon Construction for Foreign Language Tutoring.
Dorr BJ, Olsen M B.  1997.  Deriving verbal and compositional lexical aspect for NLP applications. Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics. :151-158.
Dorr BJ, Green R, Levin L, Rambow O, Farwell D, Habash N, Helmreich S, Hovy E, Miller KJ, Mitamura T et al..  2004.  Semantic annotation and lexico-syntactic paraphrase. Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC) Workshop on Building Lexical Resources from Semantically Annotated Corpora. :47-52.
Dorr BJ, Lee J, Lin D, Suh S.  1995.  Efficient parsing for Korean and English: A parameterized message-passing approach. Computational Linguistics. 21(2):255-263.
Dorr BJ, Monz C, Oard D, President S, Zajic D, Schwartz R.  2004.  Extrinsic Evaluation of Automatic Metrics for Summarization.
Dorr BJ, Jordan PW, Benoit JW.  1998.  A Survey of Current Paradigms in Machine Translation.
Dorr BJ, Lin D, Levow G-A.  2002.  Construction of a Chinese-English Verb Lexicon for Embedded Machine Translation in Cross-Language Information Retrieval.
Dorr BJ, Voss C.  1994.  The Case for a MT Developers’ Tool with a Two-Component View of the Interlingua. Proceedings of the First Conference of the Association for Machine Translation in the Americas. :40-47.
Dorr BJ, Pearl L, Hwa R, Habash N.  2002.  Improved Word-Level Alignment: Injecting Knowledge about MT Divergences.
Dorr BJ, Garman J, Weinberg A.  1994.  From syntactic encodings to thematic roles: Building lexical entries for interlingual MT. Machine Translation. 9(3):221-250.
Dorr BJ, Voss CR.  1993.  Machine Translation of Spatial Expressions: Defining the Relation betweenan Interlingua and a Knowledge Representation System. IN PROCEEDINGS OF TWELFTH CONFERENCE OF THE AMERICAN ASSOCIATION FOR ARTIFICIAL IN℡LIGENCE. :374-379.
Dorr BJ, Ayan NF, Habash N.  2004.  Divergence Unraveling for Word Alignment.... Natural Language Engineering.
Dorr BJ.  1987.  UNITRAN: an interlingual approach to machine translation. Proceedings of the Sixth Conference of the American Association of Artificial Intelligence. :534-539.
Dorr BJ.  1988.  A Lexical Conceptual Approach to Generation for Machine Translation.
Dorr BJ.  1993.  Interlingual machine translation A parameterized approach. Artificial Intelligence. 63(1–2):429-492.
Dorr BJ, Palmer M.  1995.  Building a LCS-Based Lexicon in TAGs. Proceedings of the AAAI-95 Spring Symposium Series, Representation and Acquisition of Lexical Knowledge: Polysemy, Ambiguity, and Generativity, Stanford, CA, March. :27-29.
Dorr BJ.  1991.  Solving divergences in machine translation.

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